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Al Dairi, J S S (2017) The design and development of a knowledge-based lean six sigma maintenance system for sustainable buildings, Unpublished PhD Thesis, , University of Bradford.

Anwar, W (2019) Development of multiple linear regression model and rule based decision support system to improve supply chain management of road construction projects in disaster regions, Unpublished PhD Thesis, , University of Bradford.

  • Type: Thesis
  • Keywords: decision support; artificial intelligence; communication; decision making; integration; road construction; supply chain management; project performance; regression model
  • ISBN/ISSN:
  • URL: http://hdl.handle.net/10454/19403
  • Abstract:
    Supply chain operations of construction industry including road projects in disaster regions results in exceeding project budget and timelines. In road construction projects, supply chain with poor performance can affect efficiency and completion time of the project. This is also the case of the road projects in disaster areas. Disaster areas consider both natural and man-made disasters. Few examples of disaster zones are; Pakistan, Afghanistan, Iraq, Sri Lanka, India, Japan, Haiti and many other countries with similar environments. The key factors affecting project performance and execution are insecurity, uncertainties in demand and supply, poor communication and technology, poor infrastructure, lack of political and government will, unmotivated organizational staff, restricted accessibility to construction materials, legal hitches, multiple challenges of hiring labour force and exponential construction rates due to high risk environment along with multiple other factors. The managers at all tiers are facing challenges of overrunning time and budget of supply chain operations during planning as well as execution phase of development projects. The aim of research is to develop a Multiple Linear Regression Model (MLRM) and a Rule Based Decision Support System by incorporating various factors affecting supply chain management of road projects in disaster areas in the order of importance. This knowledge base (KB) (importance / coefficient of each factor) will assist infrastructure managers (road projects) and practitioners in disaster regions in decision making to minimize the effect of each factor which will further help them in project improvement. Conduct of Literature Review in the fields of disaster areas, supply chain operational environments of road project, statistical techniques, Artificial Intelligence (AI) and types of research approaches has provided deep insights to the researchers. An initial questionnaire was developed and distributed amongst participants as pilot project and consequently results were analysed. The results' analysis enabled the researcher to extract key variables impacting supply chain performance of road project. The results of questionnaire analysis will facilitate development of Multiple Linear Regression Model, which will eventually be verified and validated with real data from actual environments. The development of Multiple Linear Regression Model and Rule Based Decision Support System incorporating all factors which affect supply chain performance of road projects in disastrous regions is the most vital contribution to the research. The significance and novelty of this research is the methodology developed that is the integration of those different methods which will be employed to measure the SCM performance of road projects in disaster areas.

Ashrafi, R M (1981) Risk analysis in management planning and project control: Probabilistic techniques are applied to the estimation, planning, forecasting and control of large capital projects to ascertain and reduce the degree of inherent risk and uncertainty, Unpublished PhD Thesis, , University of Bradford.

Clegg, S R (1974) Power in organization theory: A conceptual and emperical enquiry into rules and power in the organization, employing conversational materials collected on a construction site, Unpublished PhD Thesis, , University of Bradford.

Lazarski, A (2014) The importance of contextual factors on the accuracy of estimates in project management: An emergence of a framework for more realistic estimation process, Unpublished PhD Thesis, , University of Bradford.

Ninos, G E (1983) Control of construction contracts: analysis of systems for the control of progress, quality and cost of construction to the client, based upon six cases in building or civil engineering in the UK, Unpublished PhD Thesis, Department of Technological Management, University of Bradford.

Njoku, A I (2014) Evaluation of the impact of adherence to project governance principles on the outcome of large infrastructure projects implemented in developing economies, with Nigeria as an example, Unpublished PhD Thesis, School of Management, University of Bradford.

Prince, M W (1988) Strategic planning in construction firms: Perceptions and personal characteristics of the manager, strategic planning behaviour, and subjective performance in a large scale survey of the canadian construction industry, Unpublished PhD Thesis, , University of Bradford.